Object detection apparatus method

ABSTRACT

In an object detection apparatus, a range image generator, based on distance information indicative of distances from a given measurement point to objects in real space, generates a range image indicative of a distribution of distance information of objects located around the measurement point. A subgroup generator horizontally divides the range image into a number of column regions of prescribed width, and for each column region, generates one or more subgroups that extend continuously in a vertical direction of the range image and fall within a given range of distance information. A continuity determiner determines, for each of the subgroups, whether or not there is distance continuity between the subgroup and its horizontally adjacent subgroup in the range image. A merger merges together horizontally continuous-in-distance subgroups. An object detector detects an object in each of regions of the range image corresponding to the respective merged groups.

CROSS-REFERENCE TO RELATED APPLICATION

This application is based on and claims the benefit of priority fromearlier Japanese Patent Application No. 2015-143878 filed Jul. 21, 2015,the description of which is incorporated herein by reference.

BACKGROUND

Technical Field

The present invention relates to an apparatus and a method for detectingan object based on a range image.

Related Art

Conventionally, various object detection apparatuses for a vehicledriving assistance system have been proposed for detecting objectsaround a vehicle carrying the system to perform collision avoidancecontrol. For example, an object detection apparatus disclosed inJapanese Patent Application Laid-Open Publication No. 2014-96005 isconfigured to generate a range image based on a pair of grayscale imagesand group adjacent regions in the range image having range datarepresenting close distances. However, a grouping region made bygrouping adjacent regions may include different objects located atsubstantially the same distances from the vehicle carrying theapparatus. The object detection apparatus is configured to determinewhether or not the grouping region can be divided based on verticalbrightness differences on the range image. If the grouping region can bedivided, the apparatus detects objects in sub-regions obtained bydividing the grouping region.

The object detection apparatus divides the grouping region usingbrightness information on the grayscale image, which may increaseprocessing load. Thus, a vehicle-mounted apparatus with a limited memorycapacity and a limited memory access speed needs an increased amount oftime to detect objects, which may make it difficult to detect objects inreal time. In addition, to reduce the processing load, the objectdetection apparatus disclosed in Japanese Patent Application Laid-OpenPublication No. 2014-96005 detects objects in the grouping region of therange image, which may degrade the object detection performance.

In consideration of the foregoing, exemplary embodiments of the presentinvention are directed to providing techniques for detecting objectswhile both suppressing processing load and preventing object detectionperformance degradation in a compatible manner.

SUMMARY

In accordance with an exemplary embodiment of the present invention,there is provided an object detection apparatus including: a range imagegenerator configured to, based on distance information indicative ofdistances from a given measurement point to objects in real space,generate a range image indicative of a distribution of distanceinformation of objects located around the measurement point, a verticaldirection of the range image corresponding to an up-down direction ofthe real space; a subgroup generator configured to divide the rangeimage generated by the range image generator in a horizontal directionof the range image into a number of column regions of prescribed width,and for each column region, generate one or more subgroups that extendcontinuously in a vertical direction of the range image and fall withina given range of distance information; a continuity determinerconfigured to, for each of the subgroups generated by the subgroupgenerator, determine whether or not there is distance continuity betweenthe subgroup and its horizontally adjacent subgroup in the range image;a merger configured to merge together horizontallycontinuous-in-distance subgroups, between any pair of horizontallyadjacent subgroups of which it is determined by the continuitydeterminer that there is distance continuity, to generate a mergedgroup; and an object detector configured to detect an object in each ofregions of the range image corresponding to the respective merged groupsgenerated by the merger.

With this apparatus configured as above, based on the distanceinformation indicative of distances from a given measurement point toobjects in real space, the range image indicative of a distribution ofdistance information of the objects located around the measurement pointis generated. The range image is horizontally divided into a number ofcolumn regions of prescribed width. In each column region, one or moresubgroups are generated, each of which continuously extends in thevertical direction of the range image and falls within a given range ofdistance information. For each of the subgroups generated in the columnregions, it is determined whether or not there is distance continuitybetween the subgroup and its horizontally adjacent subgroup in the rangeimage. Horizontally continuous-in-distance subgroups are merged togetherto generate a merged group. Thus, subgroups are merged together, wherebyfor each object a merged group corresponding to the object can begenerated. Further, the merged groups can be generated using only therange image, which can suppress the processing load. An object can bedetected in each of regions of the range image corresponding to therespective merged subgroups, which can lead to higher accuracy ofdetecting objects. Therefore, objects can be detected while bothsuppressing processing load and preventing object detection performancedegradation in a compatible manner.

Further, with this apparatus configured as above, distance continuitycan be determined in the vertical direction of the range image.Thereafter, distance continuity can be determined in the horizontaldirection of the range image. This has a remarkable effect ofsuppressing the processing load in three-dimensional object detection.More specifically, the three-dimensional objects have smaller variationsin distance in the vertical direction than the other objects than thethree-dimensional objects have. Therefore, determining the variations indistance in the vertical direction prior to determining the variationsin distance in the horizontal direction can facilitate extraction of thethree-dimensional objects. The subsequent processing may be performedonly on regions where the three-dimensional objects are likely to exist.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 a block diagram of an object detection apparatus in accordancewith one embodiment of the present invention;

FIG. 2 is a top down view of a positional relationship between an ownvehicle and objects located around the own vehicle;

FIG. 3 is an example grayscale image captured in a situation shown inFIG. 2;

FIG. 4 is a range image calculated from the grayscale image shown inFIG. 3;

FIG. 5 is a top down view of a region where objects are in the vicinityof each other;

FIG. 6 is a simple grouping of regions close to each other:

FIG. 7 is an example histogram generated by dividing the range imageinto a number of column regions of prescribed width;

FIG. 8 is an example of subgroups in respective column regions;

FIG. 9 is an example of disparities of subgroups;

FIG. 10 is an example of merged groups generated by merging subgroups;

FIG. 11 is a schematic of determining distance continuity betweensubgroups;

FIG. 12 is a wall extending further away from an own vehicle in realspace depicted in a range image; and

FIG. 13 is a flowchart of merged group generation processing.

DESCRIPTION OF SPECIFIC EMBODIMENTS

The invention will now be described more fully hereinafter withreference to the accompanying drawings, in which illustrativeembodiments of the invention are shown. This invention may, however, beembodied in many different forms and should not be construed as limitedto the embodiments set forth herein; rather, these embodiments areprovided so that this disclosure will be thorough and complete, and willfully convey the scope of the invention to those skilled in the art.Like numbers refer to like elements throughout.

An object detection apparatus in accordance with one embodiment of thepresent invention is mounted in a vehicle and configured to detectobjects around the vehicle. The vehicle carrying the apparatus ishereinafter referred to as an own vehicle.

The object detection apparatus of the present embodiment will now bedescribed with reference to FIG. 1. The object detection apparatus maybe an electronic control unit (ECU) 20. The ECU 20 is configured toacquire a pair of grayscale images captured by a left camera 11 and aright camera 12 and detect objects located around the own vehicle 50based on the pair of grayscale images.

The left camera 11 and the right camera 12 may be configured as a pairof charge-coupled device (CCD) image sensors, metal-oxide semiconductor(MOS) image sensors, near infra-red sensors or other types of cameras toform a stereoscopic camera. The left camera 11 and the right camera 12may be mounted on left and right ends of a rear-view mirror of the ownvehicle 50 to capture images of an area that spans a pre-defined angularrange horizontally with respect to a traveling direction. The leftcamera 11 transmits a left grayscale image to the ECU 20 everypredetermined time interval, and the right camera 12 transmits a rightgrayscale image to the ECU 20 every predetermined time interval. Levelsof shading of the grayscale images may be indicated by brightnessvalues.

The ECU 20 may be microcomputer-based to include a central processingunit (CPU), read-only memory (ROM), a random-access memory (RAM), aninput/output (I/O) interface and other components.

As shown in FIG. 1, the ECU 20 includes, as functional blocks, an imageacquirer 21 a, a range image generator 21, a subgroup generator 22, acontinuity determiner 23, a merger 24, and an object detector 25.Functions of the image acquirer 21 a, the range image generator 21, thesubgroup generator 22, the continuity determiner 23, the merger 24, andthe object detector 25 may be implemented by the CPU executing computerprograms stored in the ROM or the like.

The image acquirer 21 a is configured to acquire a pair of left andright grayscale images from the left camera 11 and the right camera 12.

The range image generator 21 is configured to generate, from the pair ofleft and right grayscale images acquired by the image acquirer 21 a, arange image indicative of a distribution of distance information ofobjects located around the own vehicle 50 (the own vehicle 50 serving asa measurement point). For example, in the presence of a vehicle M1 (as apreceding vehicle) other than the own vehicle 50 and a bicycle Bbtraveling in the own lane (i.e., a lane in which the own vehicle istraveling) ahead of the own vehicle 50 and another vehicle M2 travelingin an oncoming lane, the left camera 11 and the right camera 12 willgenerate grayscale images as shown in FIG. 3. The grayscale image shownin FIG. 3 is an example grayscale image captured by either one of theleft camera 11 and the right camera 12. A positional difference in awidthwise direction of the own vehicle 50 between the left camera 11 andthe right camera 12 causes a disparity between the grayscale imagescaptured by the left camera 11 and the right camera 12. For a givenobject, there is a one-to-one correspondence between the disparity forthe object and a distance from the principal points of the left camera11 and the right camera 12 to the object. That is, the disparityprovides distance information that is information indicative of thedistance from the own vehicle 50 to the object in real space. The rangeimage is indicative of a distribution of disparities of the objectslocated around the own vehicle 50.

The range image generator 21 is configured to, using a well-knowntechnique, calculate the disparity between the pair of left and rightgrayscale images for each prescribed pixel block. The range imagegenerator 21 generates a range image indicative of a distribution ofdisparities for the objects located around the own vehicle 50 based onthe calculated disparity between a pair of left and right grayscaleimages for each prescribed pixel block. The vertical direction of therange image corresponds to an up-down direction of the real space. FIG.4 schematically shows the range image, where an object located at agreater distance from the own vehicle 50 is shown with denser hatching.The vehicle M1 and the bicycle Bb are located at similar distances.

In the range image generated by the range image generator 21, regionscorresponding to similar distances are grouped together. For eachgrouping of regions corresponding to similar distances, a groupingregion is defined as a region including the grouping of regions.Detecting objects in each grouping region allows objects located atdifferent distances from the own vehicle 50 to be detected separately.However, as shown in FIG. 5, grouping together objects that are close toeach other in three dimensions in a simple manner may cause objectsincluded in a common circle to be grouped together. In such a manner, asshown in FIG. 6, the vehicle M1 and the bicycle Bb will be groupedtogether in the range image. Thus, regions corresponding to actuallydifferent objects may be over-grouped together, which may degrade objectdetection performance. Dividing each grouping region by distance usingbrightness information of the grayscale image may lead to excessiveprocessing load, which may reduce a response speed in object detection.In the vehicle driving assistance system, to prevent collision, it isdesired to detect the objects early. Reduction in the response speed isundesirable.

In the present embodiment, two-step grouping processing is performedwith respect to distance continuity in vertical and horizontaldirections of the range image. Such a grouping technique can preventobject detection performance degradation while suppressing theprocessing load. The grouping technique of the present embodiment willnow be described.

The subgroup generator 22 horizontally divides the range image generatedby the range image generator 21 into a number of column regions ofprescribed width Dn. The subgroup generator 22 generates subgroups, eachof which continuously extends in the vertical direction of the rangeimage and falls within a given range of distance information. Theprescribed width Dn is a unit width that can prevent over-grouping, andis set such that a reference object located at a predefined distance(e.g., a few tens of 1 m) from the own vehicle 50 can be detected. Morespecifically, the prescribed width Dn may be set to less than a width ofthe reference object located at the predefined distance from the ownvehicle 50. The reference object may be a traffic sign pole or the like.

More specifically, for each column region of the range image, thesubgroup generator 22 partitions the whole range of disparity into equalpredetermined sub-ranges and votes pixels of the column region for theirrespectively corresponding sub-ranges, thereby creating a histogram asshown in FIG. 7. The subgroup generator 22 selects a sub-range ofdisparity having a relatively large number of votes (i.e., pixels) andgenerates a subgroup extending continuously in the vertical direction ofthe range image. As an example, subgroups a-w as shown in FIG. 8 aregenerated in this way. In the presence of a plurality of sub-rangeshaving a relatively large number of votes, e.g., subgroups l, m, asshown in FIG. 7, a plurality of subgroups may be generated. Eachsubgroup corresponds to a given range of disparity, that is, a givenrange of distance, in the vertical direction of the range image. Forillustration, in FIG. 8, an overlay of these subgroups is presented noton the range image, but on the grayscale image.

The continuity determiner 23 is configured to, for each of the subgroupsgenerated by the subgroup generator 22, determine whether or not thereis distance continuity to its adjacent subgroup in the horizontaldirection of the range image. The merger 24 is configured to mergehorizontally continuous-in-distance subgroups, between any pair ofhorizontally adjacent subgroups of which it is determined by thecontinuity determiner 23 that there is distance continuity, therebygenerating separate merged groups.

The continuity determination processing will now be described in moredetail with reference to FIG. 11. FIG. 11 plots locations of a subgroupas a merging reference, a subgroup to be merged (as a merge object) withthe merging reference, and the own vehicle 50 in a horizontal plane. Forexample, to determine whether or not there is distance continuity of asubgroup b with a subgroup a, it is supposed that the subgroup a servesas a merging reference and the subgroup b serves as a subgroup to bemerged. An acute angle between a reference line passing though thesubgroup a and the own vehicle 50 and an object line passing though thesubgroup a and the subgroup b is referred to as an object angle θ. Thecontinuity determiner 23 is configured to, if the object angle θ isgreater than a decision angle φ, determine that there is distancecontinuity of the subgroup b with the subgroup a in the horizontalplane.

A distance in the horizontal plane between the two subgroups spaced aprescribed width Dn apart in the horizontal direction of the range imageincreases with decreasing object angle θ. Therefore, use of the objectangle θ allows the distance continuity in the horizontal plane to bedetermined. Alternatively, as shown in FIG. 11, a decision distance d1on a further side of the merging reference from the own vehicle 50 and adecision distance d2 on a nearer side of the merging reference from theown vehicle 50 may be calculated based on the distance from the ownvehicle 50 to the merging reference, the prescribed width Dn, and thedecision angle φ, and may be used to determine the distance continuityin the horizontal plane. If the subgroup to be merged is within thedistance d1 on the further side or within a distance d2 on the nearerside, it may be determined that there is distance continuity between thetwo subgroups.

Use of the object angle θ to determine the distance continuity canprovide the following advantages.

As shown in FIG. 12, an object, such as a wall or the like, extendingfurther away from the own vehicle 50 in real space is depicted in therange image. Given positions A1, B1, C1, and D1 of the object in realspace respectively correspond to positions A2, B2, C2, and D2 on therange image. It is assumed that, in real space, a distance H2 betweenthe positions C1 and D1 in the horizontal plane is much greater than adistance H1 between the positions A1 and B1 in the horizontal plane.However, in the range image, a horizontal distance L1 between thepositions A2 and B2 and a distance L2 between the positions C2 and D2are depicted to be substantially the same.

Therefore, to determine the distance continuity of the subgroup to bemerged with the subgroup as a merging reference based on a distancebetween these subgroups in the horizontal plane, it is desirable toadaptively change the decision distances in response to variouspositional relationships between the subgroups. It is desirable to set adecision distance used to determine distance continuity with a portionbetween the points C2 and D2 to greater than a decision distance used todetermine distance continuity with a portion between the points A2 andB2. To this end, it is necessary to prepare beforehand a map storingdecision distances for various potential positional relationshipsbetween subgroups, which may consume a limited memory capacity of avehicle-mounted device. In such an approach, setting the decisiondistance to a larger one (e.g., the decision distance used to determinedistance continuity with the portion between the points C2 and D2) maycause over-grouping of different objects. For example, if a pedestrianis near the wall extending further away from the own vehicle 50, thewall and the pedestrian may be mistakenly over-grouped together to forma merged group.

In the present embodiment, the distance continuity of the subgroup to bemerged with the subgroup as a merging reference is determined using theobject angle θ. Taking into account the fact that the decision distancesd1, d2 calculated based on the distance to the merging reference, theprescribed width Dn, and the decision angle φ may change in response tothe position of the merging reference, setting only one decision angle φallows the distance continuity to be determined in response to variouspositional relationships between the subgroups. Therefore, use of theobject angle θ to determine the distance continuity on the horizontalplane between the subgroups can save memory consumption.

A method of merging subgroups will now be explained with reference toFIGS. 8-9. FIG. 9 shows a disparity for each subgroup that is given by arepresentative value, such as a median, of a disparity rangecorresponding to the subgroup.

The distance continuity between subgroups is determined from the leftend to the right end of the range image. In an example shown in FIGS. 8and 9, it is determined that there is distance continuity of thesubgroup b with the subgroup a. While it is determined that there isdistance continuity of the subgroup c with the subgroup b, it isdetermined that there is no distance continuity of the subgroup d withthe subgroup c. Therefore, the subgroups a-c are merged together togenerate a merged group (referred to as a first merged group). Thesubgroup d is separated from the subgroup c. In a similar manner,beginning with the subgroup d, it is determined iteratively that thereis distance continuity between adjacent subgroups until the subgroup gis reached. The subgroups d-g are merged together to generate anothermerged group (referred to as a second merged group), where the subgrouph is separated from the subgroup g.

Again, beginning with the subgroup h, it is determined iteratively thatthere is distance continuity between adjacent subgroups until thesubgroup k is reached. Since a column region adjacent to the subgroup kincludes two subgroups l and m. Distance continuity determinationprocessing is performed for each of the subgroups l and m. While it isdetermined that there is distance continuity between the subgroup k andthe subgroup l, it is determined that there is no distance continuitybetween the subgroup k and the subgroup m. In addition, it is determinedthat there is no distance continuity between the subgroup l and itsadjacent subgroup n. Thus, the subgroups h-l are merged together togenerate another merged group (referred to as a third merged group).Still again, beginning with the subgroup m, it is determined iterativelythat there is distance continuity between adjacent subgroups until thesubgroup w is reached. Therefore, the subgroups m-w are merged togetherto generate further another merged group (referred to as a fourth mergedgroup).

FIG. 10 shows the first to fourth merged groups generated as above andoverlaid on the range image. As shown in FIG. 10, the vehicle M1 and thebicycle Bb belong to different merged groups.

The object detector 25 detects objects in each merged group generated bythe merger 24 in the range image. With this technique, the vehicle M1and the bicycle Bb located at similar distances from the own vehicle 50can be separately detected.

Merged group generation processing to be performed in the ECU 20 willnow be described with reference to a flowchart of FIG. 13. Thisprocessing is performed iteratively every predetermined time interval.

First, in step S10, the image acquirer 21 a acquires a left grayscaleimage captured by the left camera 11. Subsequently, in step S11, theimage acquirer 21 a acquires a right grayscale image captured by theright camera 12. In step S12, the range image generator 21 generates arange image indicative of a disparity distribution from a pair of theleft and right grayscale images acquired in steps S10, S11.

Subsequently, in step S13, the pixels of the range image are grouped inprescribed width Dn by the subgroup generator 22. More specifically, thesubgroup generator 22 horizontally divides the range image into a numberof column regions of prescribed width Dn, and for each column region,generates subgroups that fall within a given range of disparity.

For each of the subgroups generated in step S13, the merger 24 mergesthe subgroup and another subgroup that is horizontally continuous indistance with the subgroup in the range image. More specifically, instep S14, the merger 24 determines, for each of the subgroups generatedin step S13, whether or not there is a subgroup to be merged with thesubgroup. For example, the merger 24 sequentially determines, from theleft end to the right end of the range image, whether or not there is asubgroup to be merged with a subgroup as a merging reference on theright side of the merging reference. If there is no more subgroup to bemerged, then the process flow ends.

If in step S14 it is determined that there is a subgroup to be merged,then in step S15 the continuity determiner 23 determines whether or notthe object angle θ defined as above is greater than the decision angleφ. If in step S15 it is determined that there is distance continuitybetween the subgroup to be merged and the merging reference, then instep S16 the merger 24 merges the merging reference and the subgroup tobe merged. Then the process flow returns to step S14, where the subgroupto be merged serves as a new merging reference.

If in step S15 it is determined that there is no distance continuitybetween the merging reference and the subgroup to be merged, thengeneration of a current merged group ends with the current mergingreference. The subgroup to be merged serves as a new merging reference.In step S17, the process flow returns to step S14, where generation of anew merged group begins with the new merging reference

The present embodiment described as above can provide the followingadvantages.

(A1) The range image indicative of a distribution of disparities ishorizontally divided into a number of column regions of prescribed widthDn. For each column region, subgroups are generated, each of whichcontinuously extends in the vertical direction of the range image andfalls within a given distance range. For each of the subgroups generatedin the column regions, it is determined there is distance continuitybetween the subgroup and its horizontally adjacent subgroup in the rangeimage. Horizontally continuous-in-distance subgroups are merged togetherto generate a merged group. Thus, the subgroups that are horizontallycontinuous in distance are merged together in the range image, wherebymerged groups can be generated, each of which corresponds to arespective object. Further, the merged groups can be generated usingonly the range image, which can suppress the processing load. An objectcan be detected in each of regions of the range image corresponding tothe respective merged subgroups, which can lead to higher accuracy ofdetecting objects. Therefore, objects can be detected while bothsuppressing processing load and preventing object detection performancedegradation in a compatible manner.

(A2) The prescribed width Dn is set to a width corresponding to a widthof a reference object at a given distance from the own vehicle in therange image, which allows the reference object to be accurately detectedat the given distance from the own vehicle and further allows an objecthaving a width greater than the width of the reference object.

(A3) The distance continuity between the subgroups is determined basedon the object angle θ that is an acute angle between the reference lineand the object line (as a decision line), which allows the distancecontinuity to be determined accurately using the single decision angleφ, regardless of any positional relationship between the subgroup to bemerged and the merging reference. This can suppress memory consumption.

(A4) Instead of using a distance transformed from the disparity, thedisparity is directly used as distance information. This allows themerged groups to be generated without transformation from the disparityto the distance. This can further suppress the processing load.

Other Embodiments

(B1) In the above embodiment, the distance continuity between thesubgroups is determined using the decision angle φ. Alternatively, if adifference in disparity between a subgroup as a merging reference and asubgroup to be merged is less than a decision disparity (correspondingto a decision distance), it may be determined that there is distancecontinuity between the two subgroups. In such an alternative embodiment,it is desirable to prepare beforehand a map storing decision disparities(or decision distances) for various potential positional relationshipsbetween subgroups.

(B2) In the above embodiment, the range image indicative of adistribution of disparities is generated. Alternatively, a range imagemay be generated that is indicative of a distribution of distancescalculated from the disparities. In such an alternative embodiment, thedistances calculated from the disparities may be used as distanceinformation.

(B3) In the above embodiment, the range image is generated using thestereoscopic camera formed of a pair of left and right cameras.Alternatively, the range image may be generated using an RGB-D camera ora structure-from-motion (SFM) technique. Still alternatively, a radar,such as a millimeter-wave radar, may be mounted on the own vehicle toscan and detect distances to objects located around the own vehicle, andthe range image may be generated by using the detected distances of theobjects.

(B4) In the above embodiment, the range image is horizontally dividedinto a number of column regions. Alliteratively, the range image isvertically divided into a number of row regions. In such an alternativeembodiment, for each of the row regions, distance continuity may bedetermined between a subgroup generated in the row region and a subgroupgenerated in it adjacent row region.

(B5) The vertical direction of the range image is perpendicular to thehorizontal direction of the range image. More generally, the verticaldirection of the range image may be a direction of the range imagecorresponding to an up-down direction in real space.

(B6) Similarly, the horizontal direction of the range image may be adirection of the range image corresponding to a left-right direction inreal space.

(B7) In the above embodiment, the range image is horizontally dividedinto a number of column regions. Alternatively, the range image may beobliquely divided into a number of oblique regions. The obliquedirection intersects with both vertical and horizontal directions of therange image. In such an alternative embodiment, for each of the obliqueregions, distance continuity may be determined between a subgroupgenerated in the oblique region and a subgroup generated in it adjacentoblique region.

What is claimed is:
 1. An object detection apparatus comprising: a rangeimage generator configured to, based on distance information indicativeof distances from a given measurement point to objects in real space,generate a range image indicative of a distribution of distanceinformation of objects located around the measurement point, a virticaldirection of the range image corresponding to an up-down direction ofthe real space; a subgroup generator configured to divide the rangeimage generated by the range image generator in a horizontal directionof the range image into a number of column regions of prescribed width,and for each column region, generate one or more subgroups that extendcontinuously in a vertical direction of the range image and fall withina given range of distance information; a continuity determinerconfigured to, for each of the subgroups generated by the subgroupgenerator, determine whether or not there is distance continuity betweenthe subgroup and its horizontally adjacent subgroup in the range image;a merger configured to merge together horizontallycontinuous-in-distance subgroups, between any pair of horizontallyadjacent subgroups of which it is determined by the continuitydeterminer that there is distance continuity, to generate a mergedgroup; and an object detector configured to detect an object in each ofregions of the range image corresponding to the respective merged groupsgenerated by the merger.
 2. The apparatus of claim 1, wherein theprescribed width is set to a width corresponding to a width of areference object at a given distance from the measurement point in therange image.
 3. The apparatus of claim 1, wherein an acute angle betweena reference line passing through a position of a subgroup as a mergingreference and the measurement point and an object line passing through aposition of a subgroup to be merged and the position of the subgroup asthe merging reference is referred to as an object angle in a horizontalplane, and the continuity determiner is configured to, if the objectangle is greater than a decision angle, determine that there is distancecontinuity between the subgroup as the merging reference and thesubgroup to be merged in the horizontal plane.
 4. The apparatus of claim1, wherein the continuity determiner is configured to, if a differencein distance information between a subgroup as a merging reference and asubgroup to be merged is less than a decision distance, determine thatthere is distance continuity between the subgroup as the mergingreference and the subgroup to be merged.
 5. The apparatus of claim 1,wherein the distance information indicates disparities between a pair ofleft and right grayscale images, and the range image generator isconfigured to generate a range image indicative of a distribution of thedisparities.
 6. An object detection apparatus comprising: a range imagegenerator configured to generate a range image based on a pair of leftand right grayscale images; a subgroup generator configured to dividethe range image into a number of prescribed regions, and in eachprescribed region, generate one or more subgroups based on distancecontinuity; a merger configured to, for each of the subgroups generatedby the subgroup generator, determine whether or not there is distancecontinuity between the subgroup and its horizontally adjacent subgroupin the range image, and merge together horizontallycontinuous-in-distance subgroups to generate a merged group; and anobject detector configured to detect an object in each of regions of therange image corresponding to the respective merged groups generated bythe merger.
 7. An object detection method comprising steps of: based ondistance information indicative of distances from a given measurementpoint to objects in real space, generating a range image indicative of adistribution of distance information of objects located around themeasurement point, a vertical direction of the range image correspondingto an up-down direction of the real space; dividing the range image in ahorizontal direction of the range image into a number of column regionsof prescribed width, and for each column region, generating one or moresubgroups that extend continuously in a vertical direction of the rangeimage and fall within a given range of distance information; for each ofthe subgroups, determining whether or not there is distance continuitybetween the subgroup and its horizontally adjacent subgroup in the rangeimage; merging together horizontally continuous-in-distance subgroups,between any pair of horizontally adjacent subgroups of which it isdetermined that there is distance continuity, thereby generating amerged group; and detecting objects in each of regions of the rangeimage corresponding to the respectively merged groups.